Paul Alper points us to this news article by Catherine Rampell about “a Kafkaesque new processing policy for select categories of visas”: If any fields on a form are left blank, it will automatically be rejected. Even if it makes no sense for the applicant to fill out that field. For example, if “Apt. Number” […]

**Political Science**category.

## “Statistical Models of Election Outcomes”: My talk this evening at the University of Michigan

At the Inter-university Consortium for Political and Social Research this evening: Statistical Models of Election Outcomes We will discuss various political and statistical aspects of election forecasts: – How accurately can elections be forecast? – What information is useful in forecasting elections? – What sorts of elections are less predictable? – To the extent that […]

## “RA Fisher and the science of hatred”

Mark Brown points us to this thoughtful article by Richard Evans regarding the controversy over Ronald Fisher, who during the twentieth century made huge contributions to genetics and statistical theory and methods and who also had serious commitments to racism and eugenics. The controversy made its way into statistics. The Committee of Presidents of Statistical […]

## Thinking about election forecast uncertainty

Some twitter action Elliott Morris, my collaborator (with Merlin Heidemanns) on the Economist election forecast, pointed me to some thoughtful criticisms of our model from Nate Silver. There’s some discussion on twitter, but in general I don’t find twitter to be a good place for careful discussion, so I’m continuing the conversation here. Nate writes: […]

## Dispelling confusion about MRP (multilevel regression and poststratification) for survey analysis

A colleague pointed me to this post from political analyst Nate Silver: At the risk of restarting the MRP [multilevel regression and poststratification] wars: For the last 3 models I’ve designed (midterms, primaries, now revisiting stuff for the general) trying to impute how a state will vote based on its demographics & polls of voters […]

## The War on Data: Now we play the price

A few years ago, Mark Palko wrote an article, The War on Data, where we wrote: The value of shared data reaches its logical extreme in high-quality, publicly available databases such as those maintained by the U.S. Census Bureau. These sources do not just support an extraordinary amount of research; they help individuals and institutions […]

## Nooooooooooooo!

When I get magazines in the mail, I put them in a pile so that later I can read them in order. I’m a few months behind on the London Review of Books so I just happened to read this article by August Kleinzahler which informs us that Donald Trump is invincible. I have no […]

## What does it take to be omniscient?

Palko points us to this comment from Josh Marshall: To put it baldly, if it’s a topic and area of study you know nothing about and after a few weeks of cramming you decide that basically everyone who’s studied the question is wrong, there’s a very small chance you’ve rapidly come upon a great insight […]

## Conflicting public attitudes on redistribution

Sociologist David Weakliem wrote recently: A Quinnipiac poll from April 2019: “Do you support or oppose raising the tax rate to 70% on an individual’s income that is over $10 million dollars?” 36% support, 59% oppose A CNN poll from February 2019: “Would you favor or oppose raising the personal income tax rate for those […]

## Blog about a column about the Harper’s letter: Here’s some discourse about a discourse about what happens when the discourse takes precedence over reality

I read this op-ed by Tom Scocca and I have some thoughts. To start with, as the above title indicates, the topic is very “meta.” Scocca’s article is a response to an open letter which is a response to criticisms of other people’s negative responses to other people’s criticisms. As a statistician, I can relate […]

## Statistical controversy on estimating racial bias in the criminal justice system

1. Background A bunch of people have asked me to comment on these two research articles: Administrative Records Mask Racially Biased Policing, by Dean Knox, Will Lowe, and Jonathan Mummolo: Researchers often lack the necessary data to credibly estimate racial discrimination in policing. In particular, police administrative records lack information on civilians police observe but […]

## No, I don’t believe that claim based on regression discontinuity analysis that . . .

tl;dr. See point 4 below. Despite the p-less-than-0.05 statistical significance of the discontinuity in the above graph, no, I do not believe that losing a close election causes U.S. governors to die 5-10 years longer, as was claimed in this recently published article. Or, to put it another way: Despite the p-less-than-0.05 statistical significance of […]

## Election odds update (Biden still undervalued but not by so much)

Last week I wrote about the discrepancy between our election forecast and the betting odds: Suppose I were to lay $1000 on Biden right now. According to Betfair it seems that, if I win, I make a profit of $840. And our model gives Biden an 88% chance of winning. But we’re modeling Biden vs. […]

## Do we really believe the Democrats have an 88% chance of winning the presidential election?

OK, enough about coronavirus. Time to talk about the election. Dhruv Madeka starts things off with this email: Someone just forwarded me your election model (with Elliott Morris and Merlin Heidemanns) for the Economist. I noticed Biden was already at 84%. I wrote a few years ago about how the time to election factors a […]

## How unpredictable is the 2020 election?

Our poll aggregation partially pools toward a “fundamentals”-based election forecast. Elliott Morris summarizes: What I did was create an index of economic growth over the past years using standardized percentages changes in 9 different variables (some of which you and Chris use in your LEI work). This gets combined with approval ratings, trial-heat polls and […]

## Improving our election poll aggregation model

Luke Mansillo saw our election poll aggregation model and writes: I had a look at the Stan code and I wondered if the model that you, Merlin Heidemanns, and Elliott Morris were implementing was not really Drew Linzer’s model but really Simon Jackman’s model. I realise that Linzer published Dynamic Bayesian Forecasting of Presidential Elections […]

## MIT’s science magazine misrepresents critics of Stanford study

I’m disappointed. MIT can and should do better. I know MIT is not perfect—even setting aside Jeffrey Epstein and the Media Lab more generally, it’s just an institution, and all institutions have flaws. But they should be able to run a competent science magazine, for chrissake. Scene 1 Last month, I received the following query […]

## Election 2020 is coming: Our poll aggregation model with Elliott Morris of the Economist

Here it is. The model is vaguely based on our past work on Bayesian combination of state polls and election forecasts but with some new twists. And, check it out: you can download our R and Stan source code and the data! Merlin Heidemanns wrote much of the code, which in turn is based on […]

## One more Bolivia election fraud fraud thing

Following up on our post on their article on Bolivia election fraud fraud, Nicolás Idrobo, Dorothy Kronick, Francisco Rodríguez write: The final OAS report on Bolivia presents a graph even worse than the rdplot you checked out in your post last November (which was from their preliminary report). Here’s their main piece of evidence for […]

## Bolivia election fraud fraud update

Last November there was a disputed presidential election in Bolivia. The Organization of American States wrote, “Given all the irregularities observed, it is impossible to guarantee the integrity of the data and certify the accuracy of the result. . . . In all likelihood, given more time to process documentation, even more irregularities would surface.” […]